Category Archives: Neuroscience

Neuroscience Antibodies & Assays Market Booming by Size, Revenue, Trend and Top Growing Companies 2026 – Vital News 24

Neuroscience Antibodies & Assays Market

New Jersey, United States, The report offers an all-inclusive and accurate research study on the Neuroscience Antibodies & Assays Market while chiefly that specialize in current and historical market scenarios. Stakeholders, market players, investors, and other market participants can significantly have the benefit of the thorough marketing research provided within the report. The authors of the report have compiled an in depth study on crucial market dynamics, including growth drivers, restraints, and opportunities. This study will help market participants to induce a decent understanding of future development of the Neuroscience Antibodies & Assays market. The report also focuses on market taxonomy, regional analysis, opportunity assessment, and vendor analysis to assist with comprehensive evaluation of the Neuroscience Antibodies & Assays market.

Neuroscience Antibodies & Assays Market was valued at USD 2.42 Billion in 2018 and is projected to reach USD 5.14 Billion by 2026, growing at a CAGR of 9.7% from 2019 to 2026.

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Top 10 Companies in the Global Neuroscience Antibodies & Assays Market Research Report:

Global Neuroscience Antibodies & Assays Market: Competitive Landscape

The research analysts who have authored this report are experts in performing competitive analysis of the global Neuroscience Antibodies & Assays market. They have deeply profiled leading as well as other players of the global Neuroscience Antibodies & Assays market with large emphasis on their market share, recent developments, business overview, markets served, and growth strategies. The report not only provides valuable insights into the competitive landscape but also concentrates on minor as well as major factors influencing the business of players. The product portfolios of all companies profiled in the report are compared in quite some detail in the product analysis section.

Global Neuroscience Antibodies & Assays Market: Segment Analysis

The global Neuroscience Antibodies & Assays market is segmented according to type, application, and region. The analysts have carefully studied each segment and sub-segment to provide a broad segmental analysis of the global Neuroscience Antibodies & Assays market. The segmentation study identifies leading segments and explains key factors supporting their growth in the global Neuroscience Antibodies & Assays market. In the regional analysis section, the report authors have shown how different regions and countries are growing in the global Neuroscience Antibodies & Assays market and have predicted their market sizes for the next few years. The segmental analysis will help companies to focus on high-growth areas of the global Neuroscience Antibodies & Assays market.

Global Neuroscience Antibodies & Assays Market: Regional Analysis

This part of the report includes detailed information of the market in different regions. Each region offers different scope to the market as each region has different government policy and other factors. The regions included in the report are North America, South America, Europe, Asia Pacific, and the Middle East. Information about different region helps the reader to understand global market better.

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Table of Content

1 Introduction of Neuroscience Antibodies & Assays Market

1.1 Overview of the Market 1.2 Scope of Report 1.3 Assumptions

2 Executive Summary

3 Research Methodology of Verified Market Research

3.1 Data Mining 3.2 Validation 3.3 Primary Interviews 3.4 List of Data Sources

4 Neuroscience Antibodies & Assays Market Outlook

4.1 Overview 4.2 Market Dynamics 4.2.1 Drivers 4.2.2 Restraints 4.2.3 Opportunities 4.3 Porters Five Force Model 4.4 Value Chain Analysis

5 Neuroscience Antibodies & Assays Market, By Deployment Model

5.1 Overview

6 Neuroscience Antibodies & Assays Market, By Solution

6.1 Overview

7 Neuroscience Antibodies & Assays Market, By Vertical

7.1 Overview

8 Neuroscience Antibodies & Assays Market, By Geography

8.1 Overview 8.2 North America 8.2.1 U.S. 8.2.2 Canada 8.2.3 Mexico 8.3 Europe 8.3.1 Germany 8.3.2 U.K. 8.3.3 France 8.3.4 Rest of Europe 8.4 Asia Pacific 8.4.1 China 8.4.2 Japan 8.4.3 India 8.4.4 Rest of Asia Pacific 8.5 Rest of the World 8.5.1 Latin America 8.5.2 Middle East

9 Neuroscience Antibodies & Assays Market Competitive Landscape

9.1 Overview 9.2 Company Market Ranking 9.3 Key Development Strategies

10 Company Profiles

10.1.1 Overview 10.1.2 Financial Performance 10.1.3 Product Outlook 10.1.4 Key Developments

11 Appendix

11.1 Related Research

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Highlights of Report

About Us:

Verified market research partners with clients to provide insight into strategic and growth analytics; data that help achieve business goals and targets. Our core values include trust, integrity, and authenticity for our clients.

Analysts with high expertise in data gathering and governance utilize industry techniques to collate and examine data at all stages. Our analysts are trained to combine modern data collection techniques, superior research methodology, subject expertise and years of collective experience to produce informative and accurate research reports.

Contact Us:

Mr. Edwyne Fernandes Call: +1 (650) 781 4080 Email: [emailprotected]

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Neuroscience Antibodies & Assays Market Booming by Size, Revenue, Trend and Top Growing Companies 2026 - Vital News 24

Neuroscience Antibodies and Assays Market to Register a Healthy CAGR Throughout 20172025 – Fusion Science Academy

The Hiv Therapeutics Market research report added by Market Study Report, LLC, provides a succinct analysis on the recent market trends. In addition, the report offers a thorough abstract on the statistics, market estimates and revenue forecasts, which further highlights its position in the industry, in tandem with the growth strategies adopted by leading industry players.

The Hiv Therapeutics market study is a well-researched report encompassing a detailed analysis of this industry with respect to certain parameters such as the product capacity as well as the overall market remuneration. The report enumerates details about production and consumption patterns in the business as well, in addition to the current scenario of the Hiv Therapeutics market and the trends that will prevail in this industry.

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What pointers are covered in the Hiv Therapeutics market research study?

The Hiv Therapeutics market report Elucidated with regards to the regional landscape of the industry:

The geographical reach of the Hiv Therapeutics market has been meticulously segmented into United States, China, Europe, Japan, Southeast Asia & India, according to the report.

The research enumerates the consumption market share of every region in minute detail, in conjunction with the production market share and revenue.

Also, the report is inclusive of the growth rate that each region is projected to register over the estimated period.

The Hiv Therapeutics market report Elucidated with regards to the competitive landscape of the industry:

The competitive expanse of this business has been flawlessly categorized into companies such as

* Boehringer Ingelheim International GmbH* Merck & Co.* ViiV Healthcare* AbbVie* F. Hoffmann-La Roche Ltd.* Teva Pharmaceutical Industries Ltd.For complete companies list, please ask for sample pages.

The information for * Company Profile* Main Business Information * SWOT Analysis * Sales, Revenue, Price and Gross Margin * Market Share

For product type segment, this report listed main product type of Hiv Therapeutics market* Product Type I* Product Type II* Product Type III

For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.* Hospitals* Clinics* Labs

For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:* North America* South America* Asia & Pacific* Europe* MEA (Middle East and Africa)

The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

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Exclusive details pertaining to the contribution that every firm has made to the industry have been outlined in the study. Not to mention, a brief gist of the company description has been provided as well.

Substantial information subject to the production patterns of each firm and the area that is catered to, has been elucidated.

The valuation that each company holds, in tandem with the description as well as substantial specifications of the manufactured products have been enumerated in the study as well.

The Hiv Therapeutics market research study conscientiously mentions a separate section that enumerates details with regards to major parameters like the price fads of key raw material and industrial chain analysis, not to mention, details about the suppliers of the raw material. That said, it is pivotal to mention that the Hiv Therapeutics market report also expounds an analysis of the industry distribution chain, further advancing on aspects such as important distributors and the customer pool.

The Hiv Therapeutics market report enumerates information about the industry in terms of market share, market size, revenue forecasts, and regional outlook. The report further illustrates competitive insights of key players in the business vertical followed by an overview of their diverse portfolios and growth strategies.

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Some of the Major Highlights of TOC covers:

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Neuroscience Antibodies and Assays Market to Register a Healthy CAGR Throughout 20172025 - Fusion Science Academy

Inscopix Real-Time Brain Mapping Technology Empowers More Than 100 Scientific Publications – Business Wire

PALO ALTO, Calif.--(BUSINESS WIRE)--Inscopix celebrates an important milestone that neuroscientists across the world using the companys brain mapping platform have collectively achieved more than 100 scientific publications that shed light on how brain circuits shape behavior and cognition, both in health and in disease.

Used by over 400 academic and industry laboratories, Inscopixs miniature microscope-based brain mapping technology enables the recording and manipulation of brain activity in thousands of neurons simultaneously in freely behaving animal subjects. This unprecedented experimental capability, bolstered by a complete solution from biological reagents to data analytics to world class scientific support, has enabled key neuroscience discoveries in areas including learning and memory, sleep, and social behavior. Some of these insights have already been leveraged in translational research for many difficult-to-treat indications, including Parkinsons disease and chronic pain.

We are really proud of the amazing research that our customers and collaborators worldwide are pioneering. To know that our platform and solutions have helped enable more than 100 publications since the first shipment of our nVista product in 2013, is extremely rewarding and inspiring, said Kunal Ghosh, Ph.D., founder and CEO of Inscopix. We are committed to our customers scientific success and we look forward to helping them catalyze new breakthroughs in our mechanistic understanding of the brain.

Inscopix will continue to celebrate this milestone throughout 2020. Congratulate the community of researchers and take part in spreading awareness about their research by following us on Facebook, LinkedIn, Instagram, YouTube and Twitter. To learn more about the technology and our recent research collaborations, visit: https://www.inscopix.com/.

About nVista and nVoke systems

nVista and nVoke systems are Inscopixs state-of-the-art miniature microscope-based solution for imaging and manipulation of large-scale neural circuit dynamics in freely behaving subjects. With nVista and nVoke, researchers at leading research institutions worldwide are pushing the frontiers of neuroscience and asking entirely new questions about how neural circuits shape cognition and behavior in health and disease. For more information, please visit: https://www.inscopix.com/nVoke.

About Inscopix, Inc.

Inscopix empowers the development of next-generation therapeutics for difficult-to-treat brain disorders by enabling innovative research and predictive preclinical therapeutic development. Driven by a North Star of overcoming historic challenges in the field, Inscopix provides validated solutions for real-time mapping of neural activity in brain circuits. These objective, quantitative and in-brain assays are catalyzing unprecedented insights into disease mechanisms and have been shown to be more accurate at predicting clinical efficacy than animal behavior when testing a therapeutic candidates capacity to bring the brain back to a normal state. Inscopixs partner and customer discoveries help decode the brain, inform deeper understanding of mechanisms of action and enable the screening of drugs based on efficacy. For more information, please visit http://www.inscopix.com.

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Inscopix Real-Time Brain Mapping Technology Empowers More Than 100 Scientific Publications - Business Wire

Alzheimer disease Symptoms are located in Biomarks and Research in Cognitive Neuroscience has found that! – Gizmo Posts 24

Researchers have marked a new research study in understanding and detecting the complex disease- Alzheimers. They have located a biomarker.

The research team belongs to the Complutense University of Madrid (UCM). M Eugenia Lpez Garca, the author of the research study and researcher from the Cognitive Neuroscience group of the UCM, said that with this research they work on finding two subnets in the form of theta and beta frequency bands and involving frontotemporal and frontal occipital regions, that are altered during evolution of Alzheimers Disease.

The research journal was published in Brain, and the theme is about the hyper synchronization and increased connectivity between brain regions, which is the main axis of changes and magnetoencephalography (MEG) as the tools used to detect it.

The research shows that patients suffering through Mild Cognitive Impairment (MCI) afterward develop Alzheimers Disease have an increase in synchronization, but as dementia starts to develop, the synchrony starts to decrease as a symptom of cortical network dysfunction.

For the research process, 54 patients having Mild Cognitive Impairment (MCI) were recruited and monitored every six months consecutively for a time span of three years. The researchers implemented magnetoencephalography records to measure the magnetic fields of the brain at the pre-phase, which is the beginning and the post phase, which the end of the study.

The biomarker is believed to help in understanding the terrible disease and making a discovery to improve knowledge about the complexity of the disease.

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Alzheimer disease Symptoms are located in Biomarks and Research in Cognitive Neuroscience has found that! - Gizmo Posts 24

Neuroscience shows whats right and wrong with AI – TechTalks

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Two separate studies, one by UK-based artificial intelligence lab DeepMind and the other by researchers in Germany and Greece, display the fascinating relations between AI and neuroscience.

As most scientists will tell you, we are still decades away from building artificial general intelligence, machines that can solve problems as efficiently as humans. On the path to creating general AI, the human brain, arguably the most complex creation of nature, is the best guide we have.

Advances in neuroscience, the study of nervous systems, provide interesting insights into how the brain works, a key component for developing better AI systems. Reciprocally, the development of better AI systems can help drive neuroscience forward and further unlock the secrets of the brain.

For instance, convolutional neural networks (CNN), one of the key contributors to recent advances in artificial intelligence, are largely inspired by neuroscience research on the visual cortex. On the other hand, neuroscientist leverage AI algorithms to study millions of signals from the brain and find patterns that would have gone. The two fields are closely related and their synergies produce very interesting results.

Recent discoveries in neuroscience show what were doing right in AI, and what weve got wrong.

A recent study by researchers at DeepMind prove that AI research (at least part of it) is headed in the right direction.

Thanks to neuroscience, we know that one of the basic mechanisms through which humans and animals learn is rewards and punishments. Positive outcomes encourage us to repeat certain tasks (do sports, study for exams, etc.) while negative results detract us from repeating mistakes (touch a hot stove).

The reward and punishment mechanism is best known by the experiments of Russian physiologist Ivan Pavlov, who trained dogs to expect food whenever they hear a bell. We also know that dopamine, a neurotransmitter chemical produced in the midbrain, plays a great role in regulating the reward functions of the brain.

Reinforcement learning, one of the hottest areas of artificial intelligence research, has been roughly fashioned after the reward/punishment mechanism of the brain. In RL, an AI agent is set to explore a problem space and try different actions. For each action it performs, the agent receives a numerical reward or penalty. Through massive trial and error and by examining the outcome of its actions, the AI agent develops a mathematical model optimized to maximize rewards and avoiding penalties. (In reality, its a bit more complicated and involves dealing with exploration and exploitation and other challenges.)

More recently, AI researchers have been focusing on distributional reinforcement learning to create better models. The basic idea behind distributional RL is to use multiple factors to predict rewards and punishments in a spectrum of optimistic and pessimistic ways. Distributional reinforcement learning has been pivotal in creating AI agents that are more resilient to changes in their environments.

The new research, jointly done by Harvard University and DeepMind and published in Nature last week, has found properties in the brain of mice that are very similar to those of distributional reinforcement learning. The AI researchers measured dopamine firing rates in the brain to examine the variance in reward prediction rates of biological neurons.

Interestingly, the same optimism and pessimism mechanism that AI scientists had programmed in distributional reinforcement learning models was found in the nervous system of mice. In summary, we found that dopamine neurons in the brain were each tuned to different levels of pessimism or optimism, DeepMinds researchers wrote in a blog post published on the AI labs website. In artificial reinforcement learning systems, this diverse tuning creates a richer training signal that greatly speeds learning in neural networks, and we speculate that the brain might use it for the same reason.

What makes this finding special is that while AI research usually takes inspiration from neuroscience discovery, in this case, neuroscience research has validated AI discoveries. It gives us increased confidence that AI research is on the right track, since this algorithm is already being used in the most intelligent entity were aware of: the brain, the researchers write.

It will also lay the groundwork for further research in neuroscience, which will, in turn, benefit the field of AI.

While DeepMinds new findings confirmed the work done in AI reinforcement learning research, another research by scientists in Berlin, this time published in Science in early January, proves that some of the fundamental assumptions we made about the brain are quite wrong.

The general belief about the structure of the brain is that neurons, the basic component of the nervous system are simple integrators that calculate the weighted sum of their inputs. Artificial neural networks, a popular type of machine learning algorithm, have been designed based on this belief.

Alone, an artificial neuron performs a very simple operation. It takes several inputs, multiplies them by predefined weights, sums them and runs them through an activation function. But when connecting thousands and millions (and billions) of artificial neurons in multiple layers, you obtain a very flexible mathematical function that can solve complex problems such as detecting objects in images or transcribing speech.

Multi-layered networks of artificial neurons, generally called deep neural networks, are the main drive behind the deep learning revolution in the past decade.

But the general perception of biological neurons being dumb calculators of basic math is overly simplistic. The recent findings of the German researchers, which were later corroborated by neuroscientists at a lab in Greece, proved that single neurons can perform XOR operations, a premise that was rejected by AI pioneers such as Marvin Minsky and Seymour Papert.

While not all neurons have this capability, the implications of the finding are significant. For instance, it might mean that a single neuron might contain a deep network within itself. Konrad Kording, a computational neuroscientist at the University of Pennsylvania who was not involved in the research, told Quanta Magazine that the finding could mean a single neuron may be able to compute truly complex functions. For example, it might, by itself, be able to recognize an object.

What does this mean for artificial intelligence research? At the very least, it means that we need to rethink our modeling of neurons. It might spur research in new artificial neuron structures and networks with different types of neurons. Maybe it might help free us from the trap of having to build extremely large neural networks and datasets to solve very simple problems.

The whole gameto come up with how you get smart cognition out of dumb neuronsmight be wrong, cognitive scientist Gary Marcus, who also spoke to Quanta, said in this regard.

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Neuroscience shows whats right and wrong with AI - TechTalks

Neuroscience-based Fresh Tri Proves "Iterative Mindset;" Drives Habit Formation and Weight Loss – Benzinga

SILICON VALLEY, Calif., Jan. 21, 2020 /PRNewswire-PRWeb/ --Fresh Tri, a rapidly growing neuroscience-based digital health company, announced today the release of Version 2 of its Fresh Tri behavior-change software, co-developed with Walmart.

The new version of the Fresh Tri habit-formation app trains users in a unique mindset to achieve sustainable weight loss. It draws on the success of a study the company conducted with Walmart associates using its app in combination with mindset training. Version 2 features a subscription-based model for employers and healthcare organizations to make the app and its interactive, live-streamed group mindset trainings available to their employees and members.

With Fresh Tri, users build new healthy-eating habits by picking a one-week practice from a menu of evidence-based behaviors. Fresh Tri teaches users to adopt the Iterative Mindset a unique, practice-and-tweak approach that Fresh Tri discovered in Walmart associates who lost significant weight and kept it off.

New mindset live video trainings are led by clinicians who provide science-based insights and inspiration as users learn and practice this mindset.

A recent Fresh Tri study demonstrated that the app, in combination with mindset training, led to statistically significant weight loss for participants an average of 7.2 pounds over 60 days. The study also demonstrated statistically significant improvements on a battery of positive psychology metrics for participants, including mindset, self-efficacy and resilience all of which are highly associated with overall health and well-being. Finally, the study achieved statistically significant habit formation according to the Self-Report Habit Index (SRHI), a peer-reviewed, validated instrument.

"We were looking for a powerful alternative to conventional behavior-change approaches such as goal-setting, behavior-tracking and incentives, which have proven fleeting or ineffective for many people," said David Hoke, Walmart's Senior Director of Associate Health and Well-being. "The formation of healthy-eating habits through Fresh Tri could be the tip of the iceberg of what's possible. This science-based model shows that not only can we help people lose weight, but also shift their mindset so that they build resilience and well-being long term."

"We launched our study with Walmart to determine whether Fresh Tri could train users at scale in the Iterative Mindset, a newly discovered approach to habit change that we found present in 100 percent of people we studied who achieved lasting weight loss," explained Fresh Tri CEO Kyra Bobinet, MD, MPH. "Not only did Fresh Tri drive weight loss and habit formation, but it did so in a compassionate way that saves time, creates ease, and avoids negative emotions like guilt and shame."

Walmart will make Fresh Tri with Mindset Live training available to its community of associates and their families. The basic app is available to all for free through the App Store and Google Play, with the ability to subscribe to the mindset-training feature. Fresh Tri is customizable to other employers and healthcare organizations seeking to support weight loss and various other types of healthy-habit changes.

About FreshTri Fresh Tri is a behavior change technology company with offerings focusing on mindset, practice and iteration that invite users to test-drive healthy habits, removing the guesswork and feelings of failure that can often accompany lifestyle changes. Fresh Tri allows users to iterate their way to success. There is no "fail" only practice and iteration. Fresh Tri uses a simple, positive approach based on the brain science of habit formation. Find out more about Fresh Tri: freshtri.com, Instagram, Facebook

SOURCE Fresh Tri

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Neuroscience-based Fresh Tri Proves "Iterative Mindset;" Drives Habit Formation and Weight Loss - Benzinga

Exclusive Research on Neuroscience Market 2020 by and Key Companies Analysis Doric Lenses Inc, GE Healthcare, Mightex Systems, Prizmatix, Noldus…

Europe Fall Detection System Market is estimated to reach USD 114.70 Million by 2025 from USD 83.59 Million in 2017, growing at a CAGR of 4.2% in the forecast period 2018 to 2025. The new market report contains data for historic years 2016, the base year of calculation is 2017 and the forecast period Data Bridge Market research released a new market study on Europe Fall Detection System Market with 100+ market data Tables, Pie Chart, Graphs & Figures spread through Pages and easy to understand detailed analysis. At present, the market is developing its presence. The data involved in this Europe Fall Detection System market report can be very necessary when it comes to dominating the market or making a mark in the market as a new emergent. Furthermore, it endows with historic data, present market trends, environment, technological innovation, upcoming technologies and the technical progress in the related industry. Europe Fall Detection System market research report forecasts the size of the Semiconductors and Electronic industry with information on key vendor revenues, development of the industry by upstream & downstream, industry progress, key companies, along with segment type & market application. This report analyses the Semiconductors and Electronic industry from top to bottom by considering myriad of aspects.

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If you are involved in the Europe Fall Detection System industry or intend to be, then this study will provide you comprehensive outlook. Its vital you keep your market knowledge up to date segmented Europe Fall Detection System Market, By Product Type (Automatic Fall Detection System, Manual Fall Detection System), By Algorithm (Simple Threshold, Machine Learning), By Component (Accelerometers & Gyroscopes, Unimodal/Bimodal Sensors, Multimodal Sensors), By System (Wearable Systems {Watches, Clip-On, Necklace}, Non-Wearable Systems, In-Home Landline System, In-Home Cellular Systems), End-User (Home Care Settings, Hospitals and Senior Assisted Living Facilities, Lone Workers, Others), By Country (Germany, France, U.K., Spain, Italy, Russia, Netherlands, Turkey, Belgium, Switzerland, Rest of Europe) Industry Trends and Forecast to 2025

Top 10 Companies in the Europe Fall Detection System Market Research Report:

Koninklijke Philips N.V., Intel Corporation, VitalConnect, Blue Willow Systems, LifeCall, Williamson Corporation, Life Assure, Singapore Technologies Engineering Ltd, Semtech Corporation, Connect America, Tunstall, Bay Alarm Medical, MobileHelp, Mytrex, Inc., AlertOne Services, LLC and MariCare, among others.

Product definition-:The major factors driving the growth of this market are ability to assist in case of fall, growth in enhanced medical alert services, increased demand of wearable technology based fall detection system and growth in demand of smart phones. On the other hand, low acceptance of technology among elder population may hinder the growth of the market.

Europe Fall Detection System Market Country Level Analysis

The countries covered in Europe Fall Detection System market report are U.K., Germany, France, Netherlands, Russia, Belgium, Italy, Spain, Switzerland, Turkey and Rest of Europe.

Key Drivers:Europe Fall Detection System Market

Some of the key factors driving the market for Europe fall detection system are ability to assist in case of fall, growth in enhanced medical alert services. Increased demand of wearable technology based fall detection system and growth in demand of smart phones are the other factor which will drive the demand of Europe fall detection system market.

Strategic Key Insights Of The Europe Fall Detection System Report: Production Analysis Production of the Patient Handling Equipment is analyzed with respect to different regions, types and applications. Here, price analysis of various Europe Fall Detection System Market key players is also covered.

Sales and Revenue Analysis Both, sales and revenue are studied for the different regions of the Europe Fall Detection System Market. Another major aspect, price, which plays an important part in the revenue generation, is also assessed in this section for the various regions.

Supply and Consumption In continuation of sales, this section studies supply and consumption for the Europe Fall Detection System Market. This part also sheds light on the gap between supply and consumption. Import and export figures are also given in this part.

Competitors In this section, various Europe Fall Detection System industry leading players are studied with respect to their company profile, product portfolio, capacity, price, cost, and revenue.

Analytical Tools The Europe Fall Detection System Market report consists the precisely studied and evaluated information of the key players and their market scope using several analytical tools, including SWOT analysis, Porters five forces analysis, investment return analysis, and feasibility study. These tools have been used to efficiently study the growth of the major industry participants.

The 360-degree Europe Fall Detection System overview based on a and regional level. Market share, value, volume, and production capacity is analyzed on , regional and country level. And a complete and useful guide for new market aspirants

Facilitates decision making in view of noteworthy and gauging information also the drivers and limitations available of the market.

TOC points of Europe Fall Detection System Market Report:

Thanks for reading this article; you can also get individual chapter wise section or region wise report version like North America, Europe, MEA or Asia Pacific.

Table Of Contents Is Available [emailprotected] https://www.databridgemarketresearch.com/toc/?dbmr=europe-fall-detection-system-market&DP

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Exclusive Research on Neuroscience Market 2020 by and Key Companies Analysis Doric Lenses Inc, GE Healthcare, Mightex Systems, Prizmatix, Noldus...

Miami working to connect high school girls to STEM professionals – Hamilton Journal News

OXFORD

The best way to get high school girls more interested in STEM careers is to get them together with women already established in the science, technology, engineering fields.

That was the motivation behind Miami Universitys Careers Involving Quantitative Skills (CIQS) day earlier this week that saw more than 100 teenage girls from Butler County and Greater Cincinnati high schools on Miamis Oxford campus.

The annual event is designed to expose female students to same-sex role models in STEM careers and among those teaching at Miami.

The wide variety of informative and interactive sessions introduces young women to all of the opportunities and careers opened by strong quantitative skills, said John Bailer, Miami University chair of the department of statistics.

Hands-on sessions are led by professionals from different sectors including water scientists from the Greater Cincinnati Water Works and Ohio EPA along with Miami faculty members from biology, geology, neuroscience, psychology, sports analytics and the Center for Analytics and Data Science, said Bailer.

Activities ranged from treating cloudy water to learning about facial recognition software to humanitarian mapping for disaster relief to neuroscience and learning, he said.

Nationwide the efforts to expose more girls to STEM careers has been a stable of American K-12 education the last decade but results have been mixed.

Locally, public school districts in Butler County have changed curricula in an attempt to include more STEM instructional practices they believe will capture the interests of girls.

MORE: Gifted Hamilton students are racing robots among projects in this summer program

A 2019 survey by the national Junior Achievement organization finds a recent dip in the level of interest of girls toward possibly pursuing STEM careers.

According to the Junior Achievements website, 9 percent of girls between ages of 13 and 17 are interested in careers in STEM (Science, Technology, Engineering and Math). This is down from 11 percent from a similar survey in 2018.

The decline of interest in STEM careers is disappointing given how much emphasis is being placed on promoting STEM to girls, said Jack Kosakowski, president and CEO of Junior Achievement USA. One element that may need to be emphasized more is ensuring that STEM professionals are serving as role models and working with girls in educational settings as part of these initiatives.

MORE: New type of class encourages Fairfield students to pursue passion projects

That has been the goal of Miamis event and Emma Morrish, a sophomore at Talawanda High School, said it worked.

All the sessions were beneficial and it really helped to be with an adult in a possible future career I might be interested in, said Morrish.

This (event) helps because at your high school there may not be a person who has knowledge of a career. These events are important for young women because you dont necessarily thin of women being in these type of careers, she said.

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Miami working to connect high school girls to STEM professionals - Hamilton Journal News

Brand Alchemy: A Conversation With Artist Of Science Spark Neuros Spencer Gerrol – Forbes

Data-led creativity has reached an inflection point. As a result, the era of art and commerce is giving way to a new age of art and science. We are amidst a data transformation revolution and the customer topography has never been more complex. Finding the right mix of algorithm and humanity is the Holy Grail or ultimate brand hack, no matter who you are, what youre marketing, or who you are selling to.

A Conversation with Artist of Science Spark Neuros Spencer Gerrol

A palpable need to formulate best-in-class brand alchemy is the new strategic imperative. This is the reason the past generation of artists of business I hailed in my book WE-Commerce, is quickly giving way to a new breed of executive that I am calling artists of science.

Consequently, Ive decided to launch a new Brand Alchemy Q+A series in parallel with my Ask the CMO column. Ive done this to get into the minds of this new species of leadership, as I believe they will ultimately emerge as the creative Darwinists defining the future of both business and brand.

For my latest conversation in this special series, I sat down with my friend Spencer Gerrol, CEO of Spark Neuro. Spencer is a visionary leading the charge on the new neuroscience revolution, and someone who intimately understands the elegantly symbiotic relationship creativity and science must have today. Following is a recap of our conversation:

Billee Howard: I would love to start with a very broad question, which is related to recent discussions around brands becoming too algorithmic. Now, there seems to be a course correction taking place and much discourse around how you marry humanity and science in the right way. What are your thoughts?

Spencer Gerrol: Its a great question. Lets start by reviewing the context behind how we got to this point through the history of brands working in the creative space and how that has evolved over time.

Rewind, and envision the days of Mad Men, the advertising world of the 1960s. Ads were created on gut instinct and dramatically pitching stories to brand executivesno data to speak of. Today, that sounds like blasphemy as brands have become hungry for data-driven decisions.

Next the pendulum swung in the other direction; data was king, and numbers made the decisionsbut creativity often suffered. When we see a pendulum swing, we need to look at the consequences.

The fact is that a huge part of any creative process is instinctual and that shouldnt go away. At Spark Neuro we measure emotion and one thing we emphasize is that emotion is the most powerful tool human beings have. Its not just how we process the stories we hear; it is also at the core of how people envision and create art. What we call instincts, your gut, is actually emotion doing its job to guide you.

When we fast-forward in time from Mad Men to todays data-driven companies, some natural tension arose. Many creatives pay lip service to data (and even rebel against it) and researchers have become a tool to push in the other direction.

I believe weve reached a pivotal point in finding the right balance to take us forward. You have to be data-driven, but you cant lose the sense of humanity when listening to the numbers. If we're looking at just who clicked on or watched what, that data is often devoid of understanding the core of human emotion. In order to study that emotional center, practical applications of neuroscience have made great strides.

Howard: I think that is a great place to pivot to my next question. I think it's ironic that people have been less afraid of AI because of its ability to be scientific and sort through data when it often lacked a tremendous amount of humanity, whereas people have been more afraid of neuroscience, which actually has humanity and empathy at its core. I would love you to explain how the use of neuroscience can actually bring more humanity to brands and help sharpen customer understanding.

Gerrol: The introduction of neuroscience into brand research starts with understanding the status quo of consumer research. When researchers started to introduce data, the tools at our disposal were rooted in self-report, that is, what people say. Surveys and focus groups do their best to tell us how people feel, but the methods are lacking. Group-think (everyone aligning or following a leader regardless of their true feelings), social desirability bias (people wanting to look good or not be judged and answering accordingly), and a host of other biases can steer us wrong even when we think the evidence is pointing us in the right direction.

Then there's the behavioral data; big data that tells you whos doing what. That's incredibly powerful, but by nature, big data tells you what people are doing, yet it doesn't tell you why they are doing it.

Companies can try to create models that predict those behaviors; however, at some point we need to make people feel a certain way to change or amplify behavior.

In order to be more creative, we need better science and a better way of integrating that science with the creative process. Neuroscience allows us to dig deeper into what people really feel. Its more than just what they do and its far more than what they say. We measure the underlying subconscious nature of how people process information, emotion, and decisions. That pushes the boundaries for how science can become more usefully blended in with art.

Howard: I think thats a great way of articulating what Ive been writing about a lot lately. It's not science or creative, its that you're looking at two sides of the same coin and youve got to figure out how to make them hand-in-glove. I think that's what you were saying, right?

Gerrol: Yes, it absolutely is. Science and art need to work better together. That means that as much as ever, we need emotionally intelligent people to contribute creative ideas that are worth scientifically testing, but we also need new ways to measure beyond big data that lacks empathy, or self-report that fosters biases.

Step one is getting people to understand the true impact of emotion. While we think were rational beings, at the end of the day, our emotions and our instincts are driving us. Emotion is controlling all of our perceptions, decisions, and actions. When we realize that and see how important emotion is, we then recognize that we need to be able to measure it.

All of the old ways of evaluating impact are not giving us effective data to understand that emotional layer. To get there, neuroscience unlocks the ability to measure in a way that we couldn't have done before. We can actually measure emotion, do it with second-by-second precision, and quantify what was previously unquantifiable, confidently understanding the emotional impact of a given piece of creative.

Howard: The last decade of neuroscience left a lot to be desired. There seems to be a new frontier ahead of us. I'd love if you could articulate why this is happening and how much things have changed related to the efficacy of the field?

Gerrol: Neuroscience, for all intents and purposes, is a fledgling industry with the amount we know about the human brain still barely scratching the surface. In fact, every hard science, even things like physics, start out part philosophy. Remember, there was a time when we were trying to figure out whether or not the earth was flat or round or if the earth rotated around the sun, or vice versa. Great philosophers debated about these scientific questions because we didn't yet have all the measurement tools necessary. There was this mixing of philosophy and science that eventually gave way to more hard science.

Neuroscience has been in that same realm, mixing philosophy and science. First, we debated about emotion and decision-making (and we still debate about the nature of consciousness), but eventually our measurement tools evolved.

It also goes far beyond the tools themselves. EEG, for example, is a device that measures brain activity and has been around for nearly one hundred years. However, it is also a tool that collects massive amounts of often messy data that is hard to make sense of, far more than even the most brilliant scientist can manage manually.

With EEG you are looking at the brain releasing electricity through your scalp, at very small amounts, in different locations, with different frequencies, and different amplitudes of electricity. Meanwhile, every time somebody blinks, clenches their jaw, or any muscle movement or electrical interference creates noise in the data. Now computational power is leagues beyond what it was even just a few years ago and data science has allowed us to leapfrog what was possible before.

In our new world, we have the ability to clean out those noisy artifacts, train algorithms using a data-driven process through machine learning, and do so real-time as the data is being collectedno more waiting weeks for data processing. We quite literally process emotional reactions live as they are coming straight from your brain.

Howard: These advances are so exciting and its amazing to see how far practical applications of neuroscience have come. With all of these advances, what should we be careful of?

Gerrol: Yes, the science has come a long way, but buyer beware. There are still, perhaps more than ever, people peddling snake oil. I sometimes compare it to buying a bottle of wine as someone like me who is not a wine connoisseur. When I go to buy a bottle of wine, I look at the label, I look at the price and I think, OK. this one's a little more expensive than that one and the label looks nice, so I'll buy it. But, I don't really know if its a good bottle as I'm not a wine expert. Similarly, because neuroscience is such a complex topic, people should be skeptical and be able to come at any of us in this industry and ask the hard questions.

If you smell B.S. its likely you might be onto something. Your emotions, as usual, are probably telling you something valuable. We need to continue to be aware of that, because much like I'm not a wine connoisseur, your customer is likely not a neuroscientist. We need to make sure that we hold the industry to a high standard.

Howard: All terrific points. Thanks for so clearly explaining all of that. Last question. I think of you as an artist of science and Id love to hear your thoughts on what the relationship between creatives and scientists needs to look like as we move forward.

Gerrol: Thank you Billee. I appreciate that and am looking forward to our future collaboration together through that lens.

If you look at how research and creative have evolved, its different across different industries. I've been a part of the user experience industry for over 15 years, then the advertising industry, and the entertainment world, which are all totally different animals when it comes to research. If you talk about research to support designing a better website or app, you don't get much pushback on using data to help drive the decisions. Because web design and app design grew up within a data-driven age, it's less of a confrontational relationship and more of a symbiotic relationship.

With advertising, on the other hand, and even more so in Hollywood, there can be tension between research and creative. Advertising didn't grow up with science as part of the process. Science came later and the type of science being used is typically rooted in self-reported opinions. Think of the old Henry Ford adage, If I had asked people what they wanted, they would have said faster horses.

Artists naturally dont want the opinions of every person in the focus group to be treated like their creative director. In fact, all of that feedback can create an aversion to risk and water down the art. So the industry produces too much of the same and not enough stands out.

This has led to a new opportunity in todays world where relationship creatives and scientists can once again be symbiotic. We, as scientists, should respect and admire the emotional instincts that create great art. Instead of stepping on toes with peoples rationalized opinions, we can now provide a measurement that hits at the heart of what creatives really care aboutare people emotionally engaged?

This allows us to empower creatives with data that they can make actionable. We have reached a point where neuroscience can be the tool that creatives lean on to find opportunities to confidently try new things, take risks, and reinforce great storytelling instead of watering down the art.

Read more:
Brand Alchemy: A Conversation With Artist Of Science Spark Neuros Spencer Gerrol - Forbes

These Breakthroughs Made the 2010s the Decade of the Brain – Qrius

I rarely use the words transformative or breakthrough for neuroscience findings. The brain is complex, noisy, chaotic, and often unpredictable. One intriguing result under one condition may soon fail for a majority of others. Whats more, paradigm-shifting research trends often require revolutionary tools. When were lucky, those come once a decade.

But I can unabashedly say that the 2010s saw a boom in neuroscience breakthroughs that transformed the field and will resonate long into the upcoming decade.

In 2010, the idea that wed be able to read minds, help paralyzed people walk again, incept memories, or have multi-layered brain atlases was near incomprehensible. Few predicted that deep learning, an AI model loosely inspired by neural processing in the brain, would gain prominence and feed back into decoding the brain. Around 2011, I asked a now-prominent AI researcher if we could automatically detect dying neurons in a microscope image using deep neural nets; we couldnt get it to work. Today, AI is readily helping read, write, and map the brain.

As we cross into the next decade, it pays to reflect on the paradigm shifts that made the 2010s the decade of the brain. Even as a boo humbug skeptic Im optimistic about the next decade for solving the brains mysteries: from genetics and epigenetics to chemical and electrical communications, networks, and cognition, well only get better at understanding and tactfully controlling the supercomputer inside our heads.

Weve covered brain-computer interfaces (BCIs) so many times even my eyes start glazing over. Yet I still remember my jaw dropping as I watcheda paralyzed man kick off the 2014 World Cupin a bulky mind-controlled exosuit straight out ofEdge of Tomorrow.

Flash forward a few years, and scientists have already ditched the exosuit for an implanted neural prosthesis that replaces severed nerves to re-establish communication between the brains motor centers and lower limbs.

The rise in BCIs owes much tothe BrainGate project, which worked tirelessly to decode movement from electrical signals in the motor cortex, allowingparalyzed patients to use a tablet with their mindsoroperate robotic limbs. Today, prosthetic limbs coated with sensors can feed back into the brain, giving patients mind-controlled movement, sense of touch, and an awareness of where the limb is in space. Similarly, by decoding electrical signals in the auditory or visual cortex, neural implants can synthesize a persons speech by reconstructing what theyre hearing or re-create images of what theyre seeingor even of what theyre dreaming.

For now, most BCIsespecially those that require surgical implantsare mainly used to give speech or movement back to those with disabilities or decode visual signals. The brain regions that support all these functions are on the surface, making them relatively more accessible and easier to decode.

But theres plenty of interest in using the same technology to target less tangible brain issues, such as depression, OCD, addiction, andother psychiatric disordersthat stem from circuits deep within the brain. Several trials using implanted electrodes, for example, have shown dramatic improvement in peoplesuffering from depressionthat dont respond to pharmaceutical drugs, but the results vary significantly between individuals.

The next decade may see non-invasive ways to manipulate brain activity, such as focused ultrasound, transcranial magnetic or direct current stimulation (TMS/tDCS), and variants of optogenetics. Along with increased understanding of brain networks and dynamics, we may be able to play select neural networks like a piano and realize the dream of treating psychiatric disorders at their root.

Rarely does one biological research field get such tremendous support from multiple governments. Yet the 2010s saw an explosion in government-backed neuroscience initiatives from theUS,EU,and Japan, with China, South Korea, Canada, and Australia in the process of finalizing their plans. These multi-year, multi-million-dollar projects focus on developing new tools to suss out the brains inner workings, such as how it learns, how it controls behavior, and how it goes wrong. For some, the final goal is to simulate a working human brain inside a supercomputer, forming an invaluable model for researchers to test out their hypothesesand maybe act as a blueprint for one day reconstructing all of a persons neural connections, called the connectome.

Even as initial announcementsweremet with skepticismwhat exactly is the project trying to achieve?the projects allowed something previously unthinkable. The infusion of funding provided a safety blanket to develop new microscopy tools to ever-more-rapidly map the brain, resulting in a toolkit of new fluorescent indicators that track neural activation and map neural circuits. Even rudimentary simulations have generated virtual epilepsy patients to help more precisely pinpoint sources of seizures. A visual prosthesis to restore sight,a memory prosthesisto help those with faltering recall, anda push for non-invasive waysto manipulate human brains all stemmed from these megaprojects.

Non-profit institutions such as the Allen Institute for Brain Science have also joined the effort, producingmap after mapat different resolutions of various animal brains. The upcoming years will see individual brain maps pieced together into comprehensive atlases that cover everything from genetics to cognition, transforming our understanding of brain function from paper-based 2D maps into multi-layered Google Maps.

In a way, these national programs ushered in the golden age of brain science, bringing talent from other disciplinesengineers, statisticians, physicists, computer scientistsinto neuroscience. Early successes will likely drive even more investment in the next decade, especially as findings begin translating into actual therapies for people who dont respond to traditional mind-targeting drugs. The next decade will likely see innovative new tools that manipulate neural activity more precisely and less-invasively than optogenetics. The rapid rise in the amount of data will also mean that neuroscientists will quickly embrace cloud-storage options for collaborative research and GPUs and more powerful computing cores to process the data.

First, brain to AI. The physical structure and information flow in the cortex inspired deep learning, the most prominent AI model today. Ideas such as hippocampal replaythe brains memory center replays critical events in fast forward during sleep to help consolidate memoryalso benefit AI models.

In addition, the activation patterns of individual neurons merged with materials science to build neuromorphic chips, or processors thatfunction more like the brain, rather than todays silicon-based chips. Althoughneuromorphic chipsremain mainly an academic curiosity, theyhave the potentialto perform complicated, parallel computations at a fraction of the energy used by processors today. As deep neural nets get ever-more power hungry, neuromorphic chips may present a welcome alternative.

In return, AI algorithms that closely model the brain are helping solve long-time mysteries of the brain, such ashow the visual cortex processes input. In a way, the complexity and unpredictability of neurobiology is shriveling thanks to these computational advancements.

Although crossovers between biomedical research and digital software have long existedthink programs that help with drug designthe match between neuroscience and AI isfar stronger and more intimate. As AI becomes more powerful and neuroscientists collaborate outside their field, computational tools will only unveil more intricacies of neural processing, including more intangible aspects such as memory, decision-making, or emotions.

I talk a bunch about the brains electrical activity, but supporting that activity are genes and proteins. Neurons also arent a uniform bunch; multiple research groups are piecing together a whos who of the brains neural parts and their individual characteristics.

Although invented in the late 2000s, technologies such as optogenetics and single-cell RNA sequencing were widely adopted by the neuroscience community in the 2010s. Optogenetics allows researchers to control neurons with light, even in freely moving animals going about their lives. Add to that a whole list of rainbow-colored proteins to tag active cells, and its possible to implant memories. Single-cell RNA sequencing is the queen bee of deciphering a cells identity, allowing scientists to understand the geneticexpressionprofile of any given neuron. This tech is instrumental in figuring out the neuron populations that make up a brain at any point in timeinfancy, youth, aging.

But perhaps the crown in new tools goes to brain organoids, or mini-brains, that remarkably resemble those of preterm babies, making them excellent models of the developing brain. Organoids may be our best chance of figuring out the neurobiology of autism, schizophrenia, and other developmental brain issues that are difficult to model with mice. This decade is when scientists established a cookbook for organoids of different types; the next will see far more studies that tap into their potential for modeling a growing brain. With hard work and luck, we may finally be able to tease out the root causes of these developmental issues.

Shelly Xuelai Fan is a neuroscientist-turned-science writer. She completed her PhD in neuroscience at the University of British Columbia, where she developed novel treatments for neurodegeneration. While studying biological brains, she became fascinated with AI and all things biotech. Following graduation, she moved to UCSF to study blood-based factors that rejuvenate aged brains. She is the co-founder of Vantastic Media, a media venture that explores science stories through text and video, and runs the award-winning blog NeuroFantastic.com. Her first book, Will AI Replace Us? (Thames & Hudson) will be out April 2019.

This article was originally published in Singularity Hub

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These Breakthroughs Made the 2010s the Decade of the Brain - Qrius